Application of Genetic Algorithm for optimization of fuel management in nuclear reactors

M. Jayalal, M. Sai Baba, S. Satyamurty
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Abstract

Genetic algorithm is one of the optimization techniques, successfully applied in nuclear reactor environment for a variety of applications. Nuclear fuel management optimization is a classical nuclear engineering problem, which has been studied extensively and several techniques, including genetic algorithms, have been used for its solution. The study presented in this paper addresses the overall procedures and methods developed for the application of genetic algorithms in the optimization studies of nuclear fuel management. The result obtained from a study that explores a typical application of genetic algorithm in nuclear fuel management is also presented. Finding out of optimal number of fuel subassemblies in the core of a nuclear reactor (having power generating capacity of 500 MWe) is taken up for the study. The results demonstrate the suitability and efficiency of the algorithm in generating feasible solutions for the selected optimization problem.
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遗传算法在核反应堆燃料管理优化中的应用
遗传算法是优化技术中的一种,成功地应用于核反应堆环境中的各种应用。核燃料管理优化是一个经典的核工程问题,已被广泛研究,包括遗传算法在内的多种技术已被用于解决该问题。本文介绍了遗传算法在核燃料管理优化研究中的应用的总体程序和方法。本文还介绍了遗传算法在核燃料管理中的典型应用。研究了发电能力为500mwe的核反应堆堆芯燃料组件的最佳数量问题。结果证明了该算法对所选优化问题生成可行解的适用性和有效性。
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